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BIODESIX, INC.: diluted earnings per share

Diluted earnings per share for BIODESIX, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All BIODESIX, INC. financial histories

What this measure means

Reported earnings or loss per share under dilution rules. Antidilutive instruments may be excluded. A diluted value can equal the basic value without implying no potential dilution.

Exact concept: us-gaap:EarningsPerShareDiluted. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2021-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Reading these values

This selected numerical history matches Basic earnings per share for the same reporting intervals and original units. The accounting definitions remain distinct. Equal values do not establish that the concepts are interchangeable or explain why they match; filing dates and accessions may differ. Compare the definitions and source filings before combining them.

Context from the filing

Biodesix's 2024 and 2025 EPS reconciliation reports dollar losses and share counts in thousands, except per-share amounts. The displayed 6,470 and 7,551 therefore represent 6,470,000 and 7,551,000 weighted-average shares. Share data, share-based calculations and exercise prices are adjusted retrospectively for the one-for-20 reverse stock split effective September 15, 2025. Potential shares from options, warrants, restricted stock units and the employee stock purchase plan are excluded as anti-dilutive for the loss periods presented. Read the source filing.

Selected filing history

Diluted earnings per share in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31-4.67USD/shares2026-02-2610-K · 0001193125-26-076547
2024-01-012024-12-31-6.64USD/shares2026-02-2610-K · 0001193125-26-076547
2023-01-012023-12-31-0.64USD/shares2025-03-0310-K · 0000950170-25-030835
2022-01-012022-12-31-1.55USD/shares2024-03-0110-K · 0000950170-24-023513
2021-01-012021-12-31-1.58USD/shares2023-03-0610-K · 0000950170-23-006092

Related financial histories

Inspect the source

Entity
BIODESIX, INC. / CIK 0001439725
Captured
2026-09-20T09:04:00.212Z
SEC response SHA-256
45389712f526849caafc6e3b4a3c7ecabe8e0b3a11ea891aac8dd0ac4e135af6

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.

Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.

Use this in research

A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.

These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.

Research methodology · Execution and cost assumptions · Check backtest overfitting

Build with the open-source tools

Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0001439725.json") as response:
    record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
    print(concept["tag"], next(iter(concept["observations"])))